activity
20242026
collaborators

6 papers

cs.CL2026

SpeechRole: A Large-Scale Dataset and Benchmark for Evaluating Speech Role-Playing Agents

Changhao Jiang, Jiajun Sun, Yifei Cao +15

Speech is essential for realistic role-playing, yet existing work on role-playing agents largely centers on text, leaving Speech Role-Playing Agents (SRPAs) underexplored and witho…

cs.CL2025

EvaLearn: Quantifying the Learning Capability and Efficiency of LLMs via Sequential Problem Solving

Shihan Dou, Ming Zhang, Chenhao Huang +14

We introduce EvaLearn, a pioneering benchmark designed to evaluate large language models (LLMs) on their learning capability and efficiency in challenging tasks, a critical, yet un…

cs.CL2025

LLMEval-Med: A Real-world Clinical Benchmark for Medical LLMs with Physician Validation

Ming Zhang, Yujiong Shen, Zelin Li +13

Evaluating large language models (LLMs) in medicine is crucial because medical applications require high accuracy with little room for error. Current medical benchmarks have three…

cs.CL2025

RIVAL: Reinforcement Learning with Iterative and Adversarial Optimization for Machine Translation

Tianjiao Li, Mengran Yu, Chenyu Shi +6

Large language models (LLMs) possess strong multilingual capabilities, and combining Reinforcement Learning from Human Feedback (RLHF) with translation tasks has shown great potent…

cs.CL2025

Toward Generalizable Evaluation in the LLM Era: A Survey Beyond Benchmarks

Yixin Cao, Shibo Hong, Xinze Li +24

Large Language Models (LLMs) are advancing at an amazing speed and have become indispensable across academia, industry, and daily applications. To keep pace with the status quo, th…

cs.CL2024

EvoWiki: Evaluating LLMs on Evolving Knowledge

Wei Tang, Yixin Cao, Yang Deng +8

Knowledge utilization is a critical aspect of LLMs, and understanding how they adapt to evolving knowledge is essential for their effective deployment. However, existing benchmarks…